Cortical Up states induce the selective weakening of subthreshold synaptic inputs

Bartram, Julian; Kahn, Martin; Tuohy, Simon; Paulsen, Ole; Wilson, Tony; Mann, Edward O.

doi:10.1038/s41467-017-00748-5

Cited by 42 publications

(42 citation statements)

References 71 publications

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“…Finally, another recent study identified a potential candidate to tag the synapses that need to be protected from down‐selection, the opposite of what Arc would do. The experiments were performed in acute slices of adolescent mouse medial entorhinal cortex, which maintain UP/DOWN states like those seen during NREM sleep (Bartram et al., ). Using whole‐cell recordings from pyramidal neurons of layer 3, it was found that inputs arriving during the UP states underwent synaptic weakening unless they were paired with postsynaptic spiking.…”

Section: Molecular Candidates For Sleep‐dependent Synaptic Down‐selecmentioning

confidence: 99%

Sleep and synaptic down‐selection

Tononi

Cirelli

2019

Eur J of Neuroscience

143

107

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The synaptic homeostasis hypothesis (SHY) proposes that sleep is an essential process needed by the brain to maintain the total amount of synaptic strength under control. SHY predicts that by the end of a waking day the synaptic connections of many neural circuits undergo a net increase in synaptic strength due to ongoing learning, which is mainly mediated by synaptic potentiation. Stronger synapses require more energy and supplies and are prone to saturation, creating the need for synaptic renormalization. Such renormalization should mainly occur during sleep, when the brain is disconnected from the environment and neural circuits can be broadly reactivated off‐line to undergo a systematic but specific synaptic down‐selection. In short, according to SHY sleep is the price to pay for waking plasticity, to avoid runaway potentiation, decreased signal‐to‐noise ratio, and impaired learning due to saturation. In this review, we briefly discuss the rationale of the hypothesis and recent supportive ultrastructural evidence obtained in our laboratory. We then examine recent studies by other groups showing the causal role of cortical slow waves and hippocampal sharp waves/ripples in sleep‐dependent down‐selection of neural activity and synaptic strength. Finally, we discuss some of the molecular mechanisms that could mediate synaptic weakening during sleep.

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Section: Molecular Candidates For Sleep‐dependent Synaptic Down‐selecmentioning

confidence: 99%

Sleep and synaptic down‐selection

Tononi

Cirelli

2019

Eur J of Neuroscience

143

107

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“…Neuronal UP states are known to play an important role in the consolidation of memory (Marshall, Helgadottir, Molle, & Born, ), but the exact cellular mechanism by which UP states control storage of information in the brain is poorly understood. A recent study showed that UP state‐induced synaptic weakening of subthreshold inputs, while preserving synaptic strength of strong inputs (Bartram et al, ). This cellular mechanism causes a near‐global synaptic downscaling during slow wave sleep.…”

Section: Part 2: Single Neuron Significancementioning

confidence: 99%

Embedded ensemble encoding hypothesis: The role of the “Prepared” cell

Antic

Hines

Lytton

2018

J of Neuroscience Research

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We here reconsider current theories of neural ensembles in the context of recent discoveries about neuronal dendritic physiology. The key physiological observation is that the dendritic plateau potential produces sustained depolarization of the cell body (amplitude 10-20 mV, duration 200-500 ms). Our central hypothesis is that synaptically-evoked dendritic plateau potentials lead to a prepared state of a neuron that favors spike generation. The plateau both depolarizes the cell toward spike threshold, and provides faster response to inputs through a shortened membrane time constant. As a result, the speed of synaptic-to-action potential (AP) transfer is faster during the plateau phase. Our hypothesis relates the changes from "resting" to "depolarized" neuronal state to changes in ensemble dynamics and in network information flow. The plateau provides the Prepared state (sustained depolarization of the cell body) with a time window of 200-500 ms. During this time, a neuron can tune into ongoing network activity and synchronize spiking with other neurons to provide a coordinated Active state (robust firing of somatic APs), which would permit "binding" of signals through coordination of neural activity across a population. The transient Active ensemble of neurons is embedded in the longer-lasting Prepared ensemble of neurons. We hypothesize that "embedded ensemble encoding" may be an important organizing principle in networks of neurons.

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“…It was recently shown that sleep yields a net decrease in the firing rates of both hippocampal (Miyawaki and Diba, 2016) and frontal cortex neurons (Watson et al, 2016). These changes were likely explained by synaptic downscaling (Tononi and Cirelli, 2014), triggered in the hippocampus by sharp-wave ripples and sleep spindles during NREM sleep, and incorporated over the course of REM sleep (Miyawaki and Diba, 2016) and in the neocortex, triggered by alternating cycles of UP/DOWN states (Bartram et al, 2017;Gulati et al, 2017). In Miyawaki and Diba (2016) and Watson et al (2016) , we took trouble to evaluate firing rate changes between different epochs of the same state (e.g.…”

Section: Introductionmentioning

confidence: 99%

Neuronal firing rates diverge during REM and homogenize during non-REM

Miyawaki

Watson

Diba

2016

Preprint

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Neurons fire at highly variable innate rates and recent evidence suggests that low and high firing rate neurons display different plasticity and dynamics. Furthermore, recent publications imply possibly differing rate-dependent effects in hippocampus versus neocortex, but those analyses were carried out separately and with possibly important differences. To more effectively synthesize these questions, we analyzed the firing rate dynamics of populations of neurons in both hippocampal CA1 and frontal cortex under one framework that avoids pitfalls of previous analyses and accounts for regression-to-the-mean. We observed remarkably consistent effects across these regions. While rapid eye movement (REM) sleep was marked by decreased hippocampal firing and increased neocortical firing, in both regions firing rates distributions widened during REM due to differential changes in high-firing versus low-firing cells in parallel with increased interneuron activity. In contrast, upon non-REM (NREM) sleep, firing rate distributions narrowed while interneuron firing decreased. Interestingly, hippocampal interneuron activity closely followed the patterns observed in neocortical principal cells rather than the hippocampal principal cells, suggestive of long-range interactions. Following these undulations in variance, the net effect of sleep was a decrease in firing rates. These decreases were greater in lower-firing hippocampal neurons but higher-firing frontal cortical neurons, suggestive of greater plasticity in these cell groups. Our results across two different regions and with statistical corrections indicate that the hippocampus and neocortex show a mixture of differences and similarities as they cycle between sleep states with a unifying characteristic of homogenization of firing during NREM and diversification during REM. Significance StatementMiyawaki and colleagues analyze firing patterns across low-firing and high-firing neurons in the hippocampus and the frontal cortex throughout sleep in a framework that accounts for regression-to-the-mean. They find that in both regions REM sleep activity is relatively dominated by high-firing neurons and increased inhibition, resulting in a wider distribution of firing rates. On the other hand, NREM sleep produces lower inhibition, and results in a more homogenous distribution of firing rates. Integration of these changes across sleep results in net decrease of firing rates with largest drops in low-firing hippocampal pyramidal neurons and high-firing neocortical principal neurons. These findings provide insights into the effects and functions of different sleep stages on cortical neurons.

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Cortical Up states induce the selective weakening of subthreshold synaptic inputs

Cited by 42 publications

References 71 publications

Sleep and synaptic down‐selection

Sleep and synaptic down‐selection

Embedded ensemble encoding hypothesis: The role of the “Prepared” cell

Neuronal firing rates diverge during REM and homogenize during non-REM

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